ml-integration-patterns
Machine learning integration patterns for rRNA-Phylo covering three use cases - rRNA sequence classification (supervised learning with sklearn/PyTorch), multi-tree consensus (ensemble methods), and generative tree synthesis (GNNs/transformers). Includes feature engineering, model training, hyperparameter tuning, model serving, versioning, and evaluation metrics for bioinformatics ML workflows.
Installation and usage
Machine learning integration patterns for rRNA-Phylo covering three use cases - rRNA sequence classification (supervised learning with sklearn/PyTorch), multi-tree consensus (ensemble methods), and generative tree synthesis (GNNs/transformers). Includes feature engineering, model training, hyperparameter tuning, model serving, versioning, and evaluation metrics for bioinformatics ML workflows.
Once installed, you can use this skill by running the following command in your terminal:
skills use ml-integration-patterns